Web log cleaning for mining of web usage patterns

Web usage mining (WUM) is a type of Web mining, which exploits data mining techniques to extract valuable information from navigation behavior of World Wide Web users. The data should be preprocessed to improve the efficiency and ease of the mining process. So it is important to define before applyi...

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Veröffentlicht in:2011 3rd International Conference on Computer Research and Development Jg. 2; S. 490 - 494
1. Verfasser: Aye, T T
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2011
Schlagworte:
Algorithm design and analysis
Cleaning
Data preprocessing
Log File Analysis
Web mining
Web servers
Web Usage Mining
ISBN:1612848397, 9781612848396
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Web usage mining (WUM) is a type of Web mining, which exploits data mining techniques to extract valuable information from navigation behavior of World Wide Web users. The data should be preprocessed to improve the efficiency and ease of the mining process. So it is important to define before applying data mining techniques to discover user access patterns from Web log. The main task of data preprocessing is to prune noisy and irrelevant data, and to reduce data volume for the pattern discovery phase. This paper mainly focus on data preprocessing stage of the first phase of Web usage mining with activities like field extraction and data cleaning algorithms. Field extraction algorithm performs the process of separating fields from the single line of the log file. Data cleaning algorithm eliminates inconsistent or unnecessary items in the analyzed data.
ISBN:1612848397
9781612848396
DOI:10.1109/ICCRD.2011.5764181